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Style check, naming, complexity analysis for AI agents
Style check, naming, complexity analysis for AI agents
Valid MCP server (2 strong, 4 medium validity signals). 3 known CVEs in dependencies (0 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
8 files analyzed · 4 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-rog0x-lint": {
"args": [
"-y",
"@rog0x/mcp-lint-tools"
],
"command": "npx"
}
}
}From the project's GitHub README.
Code linting and style checking tools for AI agents, exposed as an MCP (Model Context Protocol) server.
All analysis is performed via regex and text parsing — no AST libraries required.
Check code style issues with configurable rules:
Analyze identifier naming conventions:
Measure code complexity metrics:
Detect potential dead code:
Analyze import statements:
npm install
npm run build
Add to your claude_desktop_config.json:
{
"mcpServers": {
"lint-tools": {
"command": "node",
"args": ["path/to/mcp-lint-tools/dist/index.js"]
}
}
}
npm install
npm run build
npm start
MIT
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